Research Associate

6 months ago


Cambridge, United Kingdom University of Cambridge Full time

The post-holder will be part of Professor De Angelis' team within the Population Health Theme at the MRC Biostatistics Unit (MRC-BSU) working on methodologies for nowcasting and forecasting epidemics.

The project is in collaboration with the Department of Computer Science and Technology at the University of Cambridge and the UK Health Protection Agency (UKHSA), and aims to investigate use of machine learning for prediction of infectious diseases outbreaks. Using data from routine surveillance of respiratory infections in the first instance, the postholder will explore different approaches to blending existing ordinary differential equation-based mechanistic infectious disease models with modern deep learning approaches to develop predictive models of relevant epidemic data. Challenges include the relative scarcity of relevant training data, characteristic of epidemics, and the need to appropriately quantify uncertainty in the predictions.

The Unit is actively seeking to increase diversity among its staff, including promoting an equitable representation of men and women. Applications from women, from minority ethnic groups and from those with non-standard career paths are especially encouraged. Appointment will be made on merit.

The Biostatistics Unit is committed to supporting hybrid working for all staff, but we do expect that staff will work from the office on a regular basis to help integration and to build our exceptional scientific community. Working entirely from the office is possible.

Fixed-term: The funds for this post are available for 2 years in the first instance.

The interview date for the role is: To be confirmed

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.


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